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Abstract #2913

Intensity-based Deep Learning for SPION concentration estimation in MR imaging

Alberto Di Biase1,2, Shuang Liu3, Masaki Sekino3, and Pablo Irarrázabal1,2
1Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 2Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, 3Department of Bioengineering, School of Engineering, University of Tokyo, Tokyo, Japan

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Quantitative Imaging, SPIONSPION is a contrast agent with a wide range of biomedical applications. A new Deep Learning based method is presented for the quantification of SPION from intensity images. This contrast agent cause off-resonance artifacts, distorting the image. The field map is encoded in the difference of two images taken alternating the direction of the slice selection gradient. The network was trained on simulated data. The network is based on U-net and uses only 2D convolution to process the whole 3D volume, interpreting the last dimension as filters. Results are shown in simulations and on phantoms acquired on a 7T scanner.

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Keywords